This simple app deployed to Streamlit Cloud is intended to help those reading. sustainability reporting literature to more easily isolate data-containing pages from textual pages in the report.
The script does so on the basis of the numeric density in the text searching specifically for keywords related to greenhouse gas emission reporting.
The user uploads the PDF, the program processes it and it then merges the data rich pages into a single abbreviated document, which the user can then preview online and download to their local computer.
For anyone reading these often lengthy reports, this tool might save some time in identifying where the key reporting data is. Suggested use the script could be integrated into a rag ingestion pipeline. Reducing the amount of data which Has to be converted to vector storage by a substantial amount.
keywords = ["GHG emissions", "Scope 1", "Scope 2", "Scope 3"]Page processing
for i, page in enumerate(reader.pages):
text = page.extract_text()
if any(keyword.lower() in text.lower() for keyword in keywords):
extracted_pages.append(i)
writer.add_page(page)
Daniel Rosehill
(public at danielrosehill dot com)
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